There is a growing demand for application-specific embedded processors in system-on-a-chip designs. Current tools and design methodologies often require designers to manually specialize the processor based on an application. Moreover, the use of the new complex instructions added to the processor is often left to designers' ingenuity. We present a solution that automatically groups dataflow operations in the application software as potential new complex instructions. The set of possible instructions is then automatically used for code generation combined with high-level arithmetic optimizations using symbolic algebra. Symbolic arithmetic manipulations provide a novel and effective method for instruction selection that is necessary due to the complexity of the automatically identified instructions. We have used our methodology to automatically add new instructions to Tensilica processors for a set of examples. Our results show that our tools improve designers productivity and efficiently specialize an embedded processor for the given application such that the execution time is greatly improved.

The growing market of multimedia applications has required the development of complex application-specified integrated circuits with significant data-path portions. Unfortunately, most high-level synthesis tools and methods cannot automatically synthesize data paths such that complex arithmetic library blocks are intelligently used. Namely, most arithmetic-level optimizations are not supported and they are left to the designer's ingenuity. In this paper, we show how symbolic algebra can be used to construct arithmetic-level decomposition algorithms. We introduce our tool, SymSyn, that optimizes and maps data flow descriptions into data paths using complex arithmetic components. SymSyn uses two new algorithms to find either minimal component mapping or minimal critical path delay (CPD) mapping of the data flow. In this paper, we give an overview of the proposed algorithms. We also show how symbolic manipulations such as tree-height-reduction, factorization, expansion, and Horner transformation are incorporated in the preprocessing step. Such manipulations are used as guidelines in initial library element selection to accelerate the proposed algorithms. Furthermore, we demonstrate how substitution can be used for multiexpression component sharing and CPD optimization.

With growing demand for embedded multimedia applications, time to market of embedded software has become a crucial issue. As a result, embedded software designers often use libraries that have been preoptimized for a given processor to achieve higher code quality. Unfortunately, current software design methodology often leaves high-level arithmetic optimizations and the use of complex library elements up to the designer's ingenuity. In this paper, we present a tool flow and a methodology, SymSoft, that automates the use of complex processor instructions and preoptimized software library routines using symbolic algebraic techniques. We use SymSoft to optimize a set of examples for the SmartBadgeIV (Maguire et al., 1998) portable embedded system running the Linux embedded operating system. The results of these optimizations show that by using SymSoft we can map the critical basic blocks of the benchmark examples to the StrongARM SA-1110 instruction set much more efficiently than the commercial StrongARM compiler. SymSoft is also used to map critical code sections to commercially available software libraries with complex mathematical elements such as exp or the inverse discrete cosine transform routine. Our measurements on SmartBadgeIV show that even higher performance improvements and energy savings are achieved by using these library elements. For example, the final optimized MP3 audio decoder runs four times faster than real-time playback while consuming four times less energy. Since the decoder executes faster than real-time playback, additional energy savings are now possible by using processor frequency and voltage scaling.

Embedded software designers often use libraries that have been pre-optimized for a given processor to achieve higher code quality. However, using such libraries in legacy code optimization is nontrivial and typically requires manual intervention. This paper presents a methodology that maps algorithmic constructs of the software specification to a library of complex software elements. This library-mapping step is automated by using symbolic algebra techniques. We illustrate the advantages of our methodology by optimizing an algorithmic level description of MPEG Layer III (MP3) audio decoder for the Badge4 [2] portable embedded system. During the optimization process we use commercially available libraries with complex elements ranging from simple mathematical functions such as exp to the IDCT routine. We implemented and measured the performance and energy consumption of the MP3 decoder software on Badge4 running embedded Linux operating system. The optimized MP3 audio decoder runs 300 times faster than the original code obtained from the standards body while consuming 400 times less energy. Since our optimized MP3 decoder runs 3.5 times faster than real-time, additional energy can be saved by using processor frequency and voltage scaling.

The market demand for portable multimedia applications has exploded in recent years. Unfortunately for such applications, current compilers and software optimization methods often require designers to do part of the optimization manually. Specifically, the high-level arithmetic optimizations and the use of complex instructions are left to the designers' ingenuity. In this paper, we present a tool flow, SymSoft, that automates the optimization of power-intensive algorithmic constructs using symbolic algebra techniques combined with energy profiling. SymSoft is used to optimize and tune the algorithmic level description of an MPEG Layer III (MP3) audio decoder for the SmartBadge (Maguire et al, 1998) portable embedded system. We show that our tool lowers the number of instructions and memory accesses and thus lowers the system power consumption. The optimized MP3 audio decoder software meets real-time constraints on the SmartBadge system with low energy consumption. Furthermore, the performance improves by a factor of 7.27 and the energy consumption decreases by a factor of 4.45 over the original executable specification.

Current multimedia applications require the design of data-path intensive circuits. Unfortunately, current design tools and methods support design abstraction at a level that is inferior to the expectation of designers. Namely, most arithmetic-level optimizations are not supported and they are left to the designers' ingenuity. In this paper, we show how symbolic algebra can be used to construct an arithmetic-level decomposition algorithm. We also introduce our tool, SymSyn, that performs arithmetic library mapping and optimization of data-flow descriptions into data paths using arithmetic components.

The growing market of multi-media applications has required the development of complex ASICs with significant data-path portions. Unfortunately, most high-level synthesis tools and methods cannot automatically synthesize data paths such that complex arithmetic library blocks are intelligently used. Symbolic computer algebra has been previously used to automate mapping data flow into a minimal set of complex arithmetic components. In this paper, we present extensions to the previous methods in order to find the minimal critical path delay (CPD) mapping. A new algorithm is proposed that incorporates symbolic manipulations such as tree-height-reduction, factorization, expansion, and Horner transformation. Such manipulations are used as guidelines in initial library element selection. Furthermore, we demonstrate how substitution can be used for multi-expression component sharing and critical path delay optimization.